1. Field of Invention
The present invention relates to a method and a system for recognizing plant diseases and a recording medium thereof, and more particularly to a method and a system for rapidly analyzing plant disease symptoms in order to recognize plant diseases by using an image and tone analyzing technology, and a recording medium thereof.
2. Related Art
The conventional plant diseases detection mainly uses breath sensing method (for example, laser-based photoacoustic sensing); however, it is required to sense the gas emitted by plants in an enclosed environments. In addition, the relevance between the emitted gas and plant diseases may need to have a further study, and the cost of hardware implementation of the technology is very high.
According to another conventional method, after taking photo images from a plant, an image analysis technology is used on the images to identify whether the plant has suffered for plant diseases and whether the plant leaves reveals symptoms. Taking the orchid industry as an example, according to a conventional method, image analysis and identification method is performed on an orchid image to separate an orchid leaves image from the orchid image, where it is required to use features of color and texture with a neural network analysis method to correctly find and analysis the orchid leaves image from the image, so as to identify whether the orchid has suffered plant diseases and whether the leaves have revealed symptoms. However, the method is too complex, because it is required to collect a large number of image data and to perform data training before separating the orchid leaves image from the orchid image. Therefore, the method is unable to meet the practical application requirements because of its low efficiency, incapability of displaying the result immediately, and the variations of leaves images.
In the above conventional method, leaves image is separated and analyzed to find plant disease symptoms, and the plant disease symptoms are identified to determine whether the leaves have suffered plant diseases. However, the method still has the following problems to be solved.
(1) In the conventional method, the leaves image and petals image are extracted from the image by their specific colors and textures, such that the calculation is complex in the method. In addition, much calculation time, low efficiency and unable to display the result immediately are also the problems appeared in the method.
(2) The image variations of the leaves and the petals are considerably high due to various factors such as growth conditions and shooting angles; therefore, it is required to collect a large number of leaves and petals images for data training, and get features for color, shape and texture in advance. Therefore, the method has the problems of time consuming, high cost, and low accuracy.
(3) The image analysis and determination are time consuming; therefore, the method cannot be applied to plant fields (for example, flower fields and orchid farms) or sorting system for plants or relative automatic equipment.
It can be known that, the conventional method for identifying whether a plant has suffered from diseases by using the image identification method needs to be improved.